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Abstract and 1. Introduction
2 related work and 2.1 technology relevant approach
2.2 Technology Relating Measures
2.3 Technology Models
3 data
4 methods and 4.1 proximity indices
4.2 interpolation and fitting data
4.3 Clustering
4.4 Forecasting
5 results and discussions and 5.1 general results
5.2 Case Study
5.3 Limitations and future works
6 conclusions and references
Appendix
Abstract
Identifying technological convergence with emerging technologies in Cybersecurity is an important task for the promotion of science and the care of change. Unlike previous studies focused on binary relationships between a paper and its concept characteristic in technology, our approach uses recognition scores to enhance relationships between research papers, integration -with keywords, citation rates, and collaboration status with specific technological concepts. The suggested method includes mining text and bibliometric study to develop and predict the technological indices for the technologies of eencryption using the 'OpenALEX' catalog. Our findings in the case study feature a significant scene between blockchain and public key cryptography, which is evident in increasing proximity indices. These results offer an important strategic perspective for reflective investments in these domains.
1 Introduction
At a time characterized by a technology revolution, understanding the dynamics of technological, convergence, and emergence has become essential for the promotion of science and strengthening modern economic [1–4]. While emerging technology continues to reinstate global landscapes in society, economical, and intellectual [5]A large gap exists in literature about a comprehensive volume measure for technological assessment [6, 7].
To address this critical gap, our study uses the integration of bibliometric indicators, such as collaboration, common keywords, and citations, to facilitate a multidimensional technological examination. We use the OpenALEX database, a rich source of scholar papers, to model the evolution of the technology of being a pencryption from 2002 to 2022. Unlike previous study that usually uses a binary relationship between research and the concept recognition of a specific technology, we use OpenLex technology marks. It enhances the relational grain between the research papers and specific technological concepts, thus improving the accuracy of recognition of technological convergence.
In addition, we use random forests to produce time -procedures series to estimate technological trajectory. This method allows us to identify a significant scene between the blockchain and public key cryptograpy, which aligns properly in the trend in the growing practical application of public key cryptography within the blockchain ecosystems.
By recognizing the early stages of technological scene, our study is not only supplements but also expands traditional patent study, providing a better perspective on emerging technological trends. This view can guide strategic investment and development of cybersecurity to strengthen defenses against emerging cyber threats.
The paper is arranged as follows. In Section 2, we evaluate the strengths and weaknesses of existing literature. Section 3 describes the data processing method, and section 4 presents the details of our proposed model. The results and their interpretations were shown in Section 5. Finally, Section 6 discussed the limitations of our study, potential extensions, and offered finishing comments.
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